Integrated Biomarkers to Characterize Breast Cancer Risk

描述（由申请人提供）：本提案的目的是开发、验证和整合新型生物标志物，以表征患乳腺癌或进展的风险。 我们已经组建了一支由学术和行业研究人员组成的优秀多学科团队，他们正在使用基于分子和细胞的技术进行生物标志物的开发。 我们将使用强大的临床资源（包括独特的回顾性和前瞻性数据集）进一步开发和评估它们，并将它们相互整合（交叉验证）并整合到临床决策（建模）中。 拟议的研究试图重新定义的范式，从传统的乳腺癌筛查相结合的检测/生物学特性/风险预测。 我们的假设是：1）SNP（生殖系）和蛋白质组（血清）谱可以定义乳腺癌风险并检测早期癌症，并且可以组合用于分层筛选策略; 2）指示进展和转移风险的有希望的生物标志物，包括基于组织的表达谱和循环肿瘤细胞（CTC）的检测，应该直接比较并整合以最大化关于表型和风险的信息;和3）生物标志物的组合分析不仅更有效，而且可能导致用于最佳临床应用的综合策略。 为了完成我们的工作，我们提出了4个项目：项目1：开发基于SNP和血清蛋白质组学的癌症检测谱在可触及和乳房X线摄影异常的临床评价背景下进行（原发性和继发性）和风险分析;项目2：开发基于石蜡的表达谱，使用回顾性数据集预测疾病进展风险（盖伊医院：25年随访且无全身治疗的自然史人群; UCSF综合微转移/CTC数据集; UCSF SPORE DCIS数据集）;项目3：开发和验证基于CTC的测定，包括CTC检测的领先方法;交叉验证CTC数据与基于组织的生物标志物;项目4：在前瞻性临床研究中评估有前景的生物标志物，以交叉验证检测方法，并整合到反映所检测癌症生物学特性的预测结果模型中。

DESCRIPTION (provided by applicant): The purpose of this proposal is to develop, validate and integrate novel biomarkers to characterize the risk of getting, having, or progressing with breast cancer. We have assembled a superb multidisciplinary team of academic and industry investigators who are using molecular and cell based technologies for biomarker development. We will further develop and evaluate them using powerful clinical resources, including unique retrospective and prospective data sets, and will integrate them with each other (cross validation) and into the context of clinical decision (modeling). The proposed studies attempt to redefine the paradigm from conventional breast cancer screening to combined detection/biological characterization/risk projection. Our hypotheses are that: 1) SNP (germline) and proteomic (serum) profiles can define breast cancer risk and detect early cancer, and may be combined for a tiered screening strategy; 2) Promising biomarkers indicative of risk of progression and metastasis, including tissue-based expression profiling and detection of circulating tumor cells (CTCs), should be directly compared as well as integrated to maximize information about phenotypes and risk; and 3) Combined analysis of biomarkers is not only more efficient but may lead to integrated strategies for optimal clinical application. In order to accomplish our work we propose 4 projects: Project 1: Develop SNP- and serum proteomics-based profiles for cancer detection (primary and secondary) and risk profiling in the context of clinical evaluation of palpable and mammographic abnormalities; Project 2: Develop paraffin based expression profiles to predict risk of disease progression using retrospective datasets (Guy's Hospital: natural history population with 25 yr follow-up and no systemic therapy; UCSF comprehensive micrometastases/CTC data set; UCSF SPORE DCIS data set); Project 3: Develop and validate CTC-based assays, including leading approaches for CTC detection; cross-validate CTC data with tissue-based biomarkers; and develop methods for molecular profiling of CTCs; Project 4: Evaluate promising biomarkers in a prospective clinical study for cross validation of assays and integration into predictive outcome models that reflect the biological properties of the cancer detected.